Abstract

We introduce a simpler alternative to existing automatic language identification technology and quantitatively compare its performance to that of a state-of-the-art architecture on the recognised OGI Telephone Speech (OGI TS) multilingual corpus. The comparison is performed on ten two-language tasks spanning five languages. Although the system that we propose exhibits inferior performance (65% versus 81% on a 40s utterance), such an alternative may potentially provide adequate performance where cost and complexity of current technology is prohibitive. In addition, it may serve as an avenue of investigation for improving scalability of automatic language identification systems.